• Title/Summary/Keyword: CPSO

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Wavelet Packet Image Coder Using Coefficients Partitioning For Remote Sensing Images (위성 영상을 위한 계수분할 웨이블릿 패킷 영상 부호화 알고리즘에 관한 연구)

  • 한수영;조성윤
    • Korean Journal of Remote Sensing
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    • v.18 no.6
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    • pp.359-367
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    • 2002
  • In this paper, a new embedded wavelet packet image coder algorithm is proposed for an effective image coder using correlation between partitioned coefficients. This new algorithm presents parent-child relationship for reducing image reconstruction error using relations between individual frequency sub-bands. By parent-child relationship, every coefficient is partitioned and encoded for the zerotree data structure. It is shown that the proposed wavelet packet image coder algorithm achieves low bit rates and rate-distortion. It also demonstrates higher PSNR under the same bit rate and an improvement in image compression time. The perfect rate control is compared with the conventional method. These results show that the encoding and decoding processes of the proposed coder are simpler and more accurate than the conventional ones for texture images that include many mid and high-frequency elements such as aerial and satellite photograph images. The experimental results imply the possibility that the proposed method can be applied to real-time vision system, on-line image processing and image fusion which require smaller file size and better resolution.

Couple Particle Swarm Optimization for Multimodal Functions

  • Pham, Minh-Trien;Baatar, Nyambayar;Koh, Chang-Seop
    • Proceedings of the KIEE Conference
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    • 2008.04c
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    • pp.44-46
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    • 2008
  • This paper Proposes a new couple particle swarm optimization (CPSO) for multimodal functions. In this method, main particles are generated uniformly using Faure-sequences, and move accordingly to cognition only model. If any main particle detects the movement direction which has local optimum, this particle would create a new particle beside itself and make a couple. After that, all couples move accordingly to conventional particle swarm optimization (PSO) model. If these couples tend toward the same local optimum, only the best couple would be kept and the others would be eliminated. We had applied this method to some analytic multimodal functions and successfully locate all local optima.

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Wavelet Packet Image Coder for Digital Contents Using Coefficients Partition Scan Order (계수분할을 이용한 디지털 컨텐츠의 웨이블릿 패킷 영상압축)

  • 한수영;이두수
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.3
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    • pp.47-52
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    • 2003
  • In this paper. a new wavelet packet image coder is proposed for images that include many high-frequency components using the relation between subbands. The new algorithm presents parent-child relationship for reducing image reconstruction error using relations between individual frequency subbands. By parent-child relationship, every coefficient is partitioned and encoded for the zerotree structure. It demonstrates higher PSNR under the same bit rate. These results show that the encoding process of the proposed coder is more accurate than the conventional ones for images that include many high-frequency elements.

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An Optimized PI Controller Design for Three Phase PFC Converters Based on Multi-Objective Chaotic Particle Swarm Optimization

  • Guo, Xin;Ren, Hai-Peng;Liu, Ding
    • Journal of Power Electronics
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    • v.16 no.2
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    • pp.610-620
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    • 2016
  • The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.